fitted and predict always return a vector, also for offset models (fixes

 #66 and fixes #69)

R/mboost.R

@@ -71,6 +71,8 @@ mboost_fit <- function(blg, response, weights = rep(1, NROW(response)),
     offsetarg <- offset
     if (is.null(offset))
         fit <- offset <- family@offset(y, weights)
+    if (length(fit) == 1)
+        fit <- rep(fit, NROW(y))
     u <- ustart <- ngradient(y, fit, weights)
 
     ### vector of empirical risks for all boosting iterations
@@ -257,8 +259,11 @@ mboost_fit <- function(blg, response, weights = rep(1, NROW(response)),
     RET$predict <- function(newdata = NULL, which = NULL,
                             aggregate = c("sum", "cumsum", "none")) {
 
-        if (mstop == 0)
+        if (mstop == 0) {
+            if (length(offset) == 1)
+                return(rep(offset, NROW(y)))
             return(offset)
+        }
         if (!is.null(xselect))
             indx <- ((1:length(xselect)) <= mstop)
         which <- thiswhich(which, usedonly = nw <- is.null(which))

tests/regtest-gamboost.R

@@ -339,8 +339,8 @@ mod2 <- mboost(DEXfat ~ bbs(age) + bols(waistcirc) + bbs(hipcirc),
 mod3 <- mboost(DEXfat ~ bbs(age) + bols(waistcirc) + bbs(hipcirc),
                data = bodyfat, control = boost_control(mstop = 1))
 stopifnot(is.null(coef(mod)))
-stopifnot(predict(mod) == mod$offset)
-stopifnot(fitted(mod) == mod$offset)
+stopifnot(predict(mod) == rep(mod$offset, nrow(bodyfat)))
+stopifnot(fitted(mod) == rep(mod$offset, nrow(bodyfat)))
 stopifnot(all.equal(residuals(mod), bodyfat$DEXfat - mean(bodyfat$DEXfat)))
 stopifnot(is.null(selected(mod)))
 stopifnot(all.equal(risk(mod), risk(mod2)[1]))
@@ -360,8 +360,8 @@ mod2 <- glmboost(DEXfat ~ age + waistcirc + hipcirc,
 mod3 <- glmboost(DEXfat ~ age + waistcirc + hipcirc,
                  data = bodyfat, control = boost_control(mstop = 1))
 stopifnot(is.null(coef(mod)))
-stopifnot(!is.null(predict(mod))) ## should be offset
-stopifnot(fitted(mod) == mod$offset)
+stopifnot(predict(mod) == rep(mod$offset, nrow(bodyfat)))
+stopifnot(fitted(mod) == rep(mod$offset, nrow(bodyfat)))
 stopifnot(all.equal(residuals(mod), bodyfat$DEXfat - mean(bodyfat$DEXfat), check.attributes = FALSE))
 stopifnot(is.null(selected(mod)))
 stopifnot(all.equal(risk(mod), risk(mod2)[1]))